





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_camembert import CamembertTokenizer
else:
  UpperCAmelCase__   : Optional[Any]         =       None


UpperCAmelCase__   : Tuple         =       logging.get_logger(__name__)

UpperCAmelCase__   : List[Any]         =       {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase__   : Union[str, Any]         =       {
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase__   : List[Any]         =       {
    '''camembert-base''': 5_12,
}

UpperCAmelCase__   : Any         =       '''▁'''






class 							__lowercase			(     snake_case__       ):
      __UpperCAmelCase		      =						VOCAB_FILES_NAMES
      __UpperCAmelCase		      =						PRETRAINED_VOCAB_FILES_MAP
      __UpperCAmelCase		      =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __UpperCAmelCase		      =						['''input_ids''', '''attention_mask''']
      __UpperCAmelCase		      =						CamembertTokenizer






      def __init__(		self			,							lowercase_=None			,							lowercase_=None			,							lowercase_="<s>"			,							lowercase_="</s>"			,							lowercase_="</s>"			,							lowercase_="<s>"			,							lowercase_="<unk>"			,							lowercase_="<pad>"			,							lowercase_="<mask>"			,							lowercase_=["<s>NOTUSED", "</s>NOTUSED"]			,							**lowercase_			,							)     ->       str:
       # Mask token behave like a normal word, i.e. include the space before it
       __snake_case         =			AddedToken(_UpperCAmelCase			,							lstrip=_UpperCAmelCase			,							rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase			,							_UpperCAmelCase) else mask_token

       super().__init__(
           _UpperCAmelCase			,							tokenizer_file=_UpperCAmelCase			,							bos_token=_UpperCAmelCase			,							eos_token=_UpperCAmelCase			,							sep_token=_UpperCAmelCase			,							cls_token=_UpperCAmelCase			,							unk_token=_UpperCAmelCase			,							pad_token=_UpperCAmelCase			,							mask_token=_UpperCAmelCase			,							additional_special_tokens=_UpperCAmelCase			,							**_UpperCAmelCase			,							)

       __snake_case         =			vocab_file
       __snake_case         =			False if not self.vocab_file else True






      def 			_a						(		self			,							lowercase_			,							lowercase_ = None)     ->       List[int]:

       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       __snake_case         =			[self.cls_token_id]
       __snake_case         =			[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep






      def 			_a						(		self			,							lowercase_			,							lowercase_ = None)     ->       List[int]:
       __snake_case         =			[self.sep_token_id]
       __snake_case         =			[self.cls_token_id]

       if token_ids_a is None:
        return len(cls + token_ids_a + sep) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]







      def 			_a						(		self			,							lowercase_			,							lowercase_ = None)     ->       Tuple[str]:
       if not self.can_save_slow_tokenizer:
        raise ValueError(
            'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
            'tokenizer.')

       if not os.path.isdir(_UpperCAmelCase):
        logger.error(F"Vocabulary path ({save_directory}) should be a directory")
        return
       __snake_case         =			os.path.join(
           _UpperCAmelCase			,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

       if os.path.abspath(self.vocab_file) != os.path.abspath(_UpperCAmelCase):
        copyfile(self.vocab_file			,							_UpperCAmelCase)

       return (out_vocab_file,)






'''simple docstring'''

from __future__ import annotations






def 				a  (     UpperCamelCase_    :    str      ,					UpperCamelCase_    :    list[str] | None = None      ,					UpperCamelCase_    :    dict[str, float] | None = None      ,					UpperCamelCase_    :    bool = False      ,					)       ->	tuple[int, float, str]:
		snake_case__	     =cipher_alphabet or [chr(UpperCamelCase_			) for i in range(97      ,					123			)]

		# If the argument is None or the user provided an empty dictionary
		if not frequencies_dict:
				# Frequencies of letters in the english language (how much they show up)
				snake_case__	     ={
				    'a': 0.0_8_4_9_7,
				    'b': 0.0_1_4_9_2,
				    'c': 0.0_2_2_0_2,
				    'd': 0.0_4_2_5_3,
				    'e': 0.1_1_1_6_2,
				    'f': 0.0_2_2_2_8,
				    'g': 0.0_2_0_1_5,
				    'h': 0.0_6_0_9_4,
				    'i': 0.0_7_5_4_6,
				    'j': 0.0_0_1_5_3,
				    'k': 0.0_1_2_9_2,
				    'l': 0.0_4_0_2_5,
				    'm': 0.0_2_4_0_6,
				    'n': 0.0_6_7_4_9,
				    'o': 0.0_7_5_0_7,
				    'p': 0.0_1_9_2_9,
				    'q': 0.0_0_0_9_5,
				    'r': 0.0_7_5_8_7,
				    's': 0.0_6_3_2_7,
				    't': 0.0_9_3_5_6,
				    'u': 0.0_2_7_5_8,
				    'v': 0.0_0_9_7_8,
				    'w': 0.0_2_5_6_0,
				    'x': 0.0_0_1_5_0,
				    'y': 0.0_1_9_9_4,
				    'z': 0.0_0_0_7_7,
				}
		else:
				# Custom frequencies dictionary
				snake_case__	     =frequencies_dict

		if not case_sensitive:
				snake_case__	     =ciphertext.lower()

		# Chi squared statistic values
		snake_case__	     ={}

		# cycle through all of the shifts
		for shift in range(len(UpperCamelCase_			)			):
				snake_case__	     =''

				# decrypt the message with the shift
				for letter in ciphertext:
						try:
								# Try to index the letter in the alphabet
								snake_case__	     =(alphabet_letters.index(letter.lower()			) - shift) % len(
								    UpperCamelCase_			)
								decrypted_with_shift += (
								    alphabet_letters[new_key].upper()
								    if case_sensitive and letter.isupper()
								    else alphabet_letters[new_key]
								)
						except ValueError:
								# Append the character if it isn't in the alphabet
								decrypted_with_shift += letter

				snake_case__	     =0.0

				# Loop through each letter in the decoded message with the shift
				for letter in decrypted_with_shift:
						if case_sensitive:
								snake_case__	     =letter.lower()
								if letter in frequencies:
										# Get the amount of times the letter occurs in the message
										snake_case__	     =decrypted_with_shift.lower().count(UpperCamelCase_			)

										# Get the excepcted amount of times the letter should appear based
										# on letter frequencies
										snake_case__	     =frequencies[letter] * occurrences

										# Complete the chi squared statistic formula
										snake_case__	     =((occurrences - expected) ** 2) / expected

										# Add the margin of error to the total chi squared statistic
										chi_squared_statistic += chi_letter_value
						else:
								if letter.lower() in frequencies:
										# Get the amount of times the letter occurs in the message
										snake_case__	     =decrypted_with_shift.count(UpperCamelCase_			)

										# Get the excepcted amount of times the letter should appear based
										# on letter frequencies
										snake_case__	     =frequencies[letter] * occurrences

										# Complete the chi squared statistic formula
										snake_case__	     =((occurrences - expected) ** 2) / expected

										# Add the margin of error to the total chi squared statistic
										chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
				snake_case__	     =(
				    chi_squared_statistic,
				    decrypted_with_shift,
				)

		# Get the most likely cipher by finding the cipher with the smallest chi squared
		# statistic
		def chi_squared_statistic_values_sorting_key(UpperCamelCase_    :    int			) -> tuple[float, str]:
				return chi_squared_statistic_values[key]

		snake_case__	     =min(
		    UpperCamelCase_      ,					key=UpperCamelCase_      ,					)

		# Get all the data from the most likely cipher (key, decoded message)
		(
		    (
		    snake_case__
		)     ,	(
		    snake_case__
		)     ,	
		)	     =chi_squared_statistic_values[most_likely_cipher]

		# Return the data on the most likely shift
		return (
		    most_likely_cipher,
		    most_likely_cipher_chi_squared_value,
		    decoded_most_likely_cipher,
		)




